Kong A2A and MCP Metrics: Visibility and Governance for AI Tool Adoption at Scale

Scaling the adoption of large language models (LLMs) and agentic AI from pilot programs to enterprise-wide deployments poses significant logistical challenges, particularly in ensuring that AI tools are used effectively. Kong has introduced Kong A2A and MCP Metrics within the Kong AI Gateway, offering unified visibility, governance, and business-level insights to address these challenges. The new metrics, coupled with the capabilities of Kong AI Gateway 3.14, facilitate the management of AI adoption at scale, providing insights into usage and performance, which are crucial for making informed decisions about tool deployment and optimization. These enhancements allow platform teams to track various metrics, such as request counts and latency, thus enabling targeted interventions for performance optimization and stakeholder engagement through data-driven conversations. This structured approach helps organizations manage AI tools efficiently, ensuring compliance and security, and ultimately supports a robust AI governance and adoption strategy.

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